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Jake Rozran
About Me
In addition to being a leader, dad, uncle, & data guy, I am a data & technology professional with real-world experience in data science, data analytics, data engineering, fraud detection, risk modeling, building and maintaining data teams, project management, sales, consulting, and teaching.
My passion for data and statistics has inspired me to become an Adjunct Professor of Statistics, which has improved my ability to explain complex subjects to all levels of understanding. I love to learn in general and am a data fanatic.
On a more personal note, I love being a husband, father, and uncle. I also love being active - soccer, running, cycling, hiking, lifting - and taking pictures (usually of my kids).
Professional Experience
Data Scientist Practice Lead
CivicActions
San Francisco, CA
2021
- Building a Data Science Practice Area with > $1MM revenue after 6 months; focused on data solutions, people management, sales, marketing, and project management.
- For the Centers of Medicare and Medicaid (CMS), leveraging Natural Language Processing (NLP) in the creation and evaluation of System Security Plans (SSPs) to optimize the Authority to Operate (ATO) process.
- For the Centers of Medicare and Medicaid (CMS), analyzing AWS usage to forecast annual usage and identify efficiencies.
Adjunct Professor
Villanova University
Villanova, PA
2020-2021
- Build the syllabus, lectures, assignments, and tests for undergraduate Intro to Statistics and Intro to Statistics for Biology courses.
Solutions Consultant
Socure
New York, NY
2020-2021
- Technical expert on fraud prevention, Know Your Customer (KYC)/Customer Identification Program (CIP), Socure product modules, data science, statistics, and data viz in support of the sales and onboarding processes.
Education
Beijing University of Chemical Technology
B.S. in Information and Computing Sciences
Beijing, China
2010
Thesis: Dyadic wavelet and its application in edge detection
University of Chinese Academy of Sciences
M.S. in Bioinformatics
Beijing, China
2014
Thesis: A multi-omics study for intra-individual divergence of the distributions between mRNA isoforms in mammals